Climate AI/ML Engineer for HPC & Climate Science

University of Chicago; United States; Hybrid; USD 85,000 - 105,000; Full time

Job summary

The University of Chicago is seeking a Computational Scientist – AI/ML Engineer to develop software for data acquisition, ingestion, and integration in multi-institutional research projects. The role focuses on AI/ML workflows, scalable back-end services, and climate/Earth system applications on HPC and GPU systems.

You will collaborate with faculty, postdocs, and students, contribute to training and documentation, and support grant activities.

Qualifications

• Education: college/university degree required.
• Work Experience: 2–5 years in a related discipline.
• Certifications: ---

Responsibilities

• Support computational applications and workflows for climate, atmospheric, geophysical, and earth system sciences.
• Collaborate with researchers to translate scientific challenges into scalable AI/ML and computational solutions.
• Deploy, optimize, and support AI/ML pipelines on HPC and GPU-accelerated systems.
• Optimize large-scale training and inference workflows using distributed computing frameworks and performance analysis tools.
• Assist researchers with compiling, debugging, profiling, tuning, and porting scientific applications.
• Maintain and optimize scientific software environments and datasets relevant to climate and earth system science.
• Contribute to grant proposals and collaborative research initiatives.
• Develop technical training materials and web-based documentation.

Skills

Python

C++

PyTorch

TensorFlow

Linux/UNIX

HPC

SLURM

GPU computing

NumPy

SciPy

pandas

xarray

scikit-learn

NetCDF

HDF5

Vision Transformers

Git

Docker

Education

Bachelor's degree in related field

PhD in Computer Science / Applied Mathematics / Atmospheric Science / Physics / Earth System Science

Tools

Git

Docker

Job description

The University of Chicago is seeking a Computational Scientist – AI/ML Engineer to develop software for data acquisition, ingestion, and integration in multi-institutional research projects. The role focuses on AI/ML workflows, scalable back-end services, and climate/Earth system applications on HPC and GPU systems.

You will collaborate with faculty, postdocs, and students, contribute to training and documentation, and support grant activities.